A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
In recent years there has been a growing interest in studying evolutionary algorithms for dynamic optimization problems due to its importance in real world applications. Several a...
We consider multivariate density estimation with identically distributed observations. We study a density estimator which is a convex combination of functions in a dictionary and ...
In recent years, interest in studying evolutionary algorithms (EAs) for dynamic optimization problems (DOPs) has grown due to its importance in real-world applications. Several app...
We consider a class of learning problems regularized by a structured sparsity-inducing norm defined as the sum of 2- or ∞-norms over groups of variables. Whereas much effort ha...